梳理58项研究，总结ChatGPT用户体验评估方法与方向
ChatGPT and U(X): A Rapid Review on Measuring the User Experience
- 系统分析58项研究的变量设计与测量方法
- 发现当前评估存在标准不一、覆盖不全等问题
- 提出两个框架，助研究者规范评估流程
自2022年发布以来，由大语言模型（LLM）驱动的ChatGPT已彻底改变人机交互方式。尽管全球已有数百万用户使用，但对其用户体验（UX）的系统性评估路径仍不清晰。本文基于58项研究的快速综述，聚焦被操纵的自变量（IVs）、测量的因变量（DVs）及评估方法。研究揭示了当前量化评估中的趋势、空白与初步共识。本工作为整合现有评估方法迈出第一步，提出了推进标准化与覆盖面的紧迫方向，并构建了两个初步框架，以指导未来研究与工具开发。旨在通过赋能研究人员与实践者，优化用户与ChatGPT等基于LLM系统的交互体验。
原文摘要 · Abstract (English)
ChatGPT, powered by a large language model (LLM), has revolutionized everyday human-computer interaction (HCI) since its 2022 release. While now used by millions around the world, a coherent pathway for evaluating the user experience (UX) ChatGPT offers remains missing. In this rapid review (N = 58), I explored how ChatGPT UX has been approached quantitatively so far. I focused on the independent variables (IVs) manipulated, the dependent variables (DVs) measured, and the methods used for measurement. Findings reveal trends, gaps, and emerging consensus in UX assessments. This work offers a first step towards synthesizing existing approaches to measuring ChatGPT UX, urgent trajectories to advance standardization and breadth, and two preliminary frameworks aimed at guiding future research and tool development. I seek to elevate the field of ChatGPT UX by empowering researchers and practitioners in optimizing user interactions with ChatGPT and similar LLM-based systems.
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